FaceTimeMap: Multi-Level Bitmap Index for Temporal Querying of Faces in Videos

Buddha Shrestha, Haeyong Chung and Ramazan S. Aygün
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Buddha Shrestha: University of Alabama in Huntsville, Huntsville, USA
Haeyong Chung: University of Alabama in Huntsville, Huntsville, USA
Ramazan S. Aygün: University of Alabama in Huntsville, Huntsville, USA

International Journal of Multimedia Data Engineering and Management (IJMDEM), 2019, vol. 10, issue 2, 37-59

Abstract: In this article, the authors study bitmap indexing for temporal querying of faces that appear in videos. Since the bitmap index is originally designed to select a set of records that satisfy a value in the domain of the attribute, there is no clear strategy for how to apply it for temporal querying. Accordingly, the authors introduce a multi-level bitmap index that the authors call “FaceTimeMap” for temporal querying of faces in videos. The first level of the FaceTimeMap index is used for determining whether a person appears in a video or not, whereas the second level of the index is used for determining intervals when a person appears. First, the authors analyze the co-appearance query where two or more people appear simultaneously in a video, and then examine next-appearance query where a person appears right after another person. In addition, to consider the gap between the appearance of people, the authors study eventual- and prior-appearance queries. Queries are satisfied by applying bitwise operations on the FaceTimeMap index. The authors provide some performance studies associated with this index.

Date: 2019
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